CDO Data Quality Management 1 — Questions and Answers
Question 1: What is the primary purpose of a Data Quality Management (DQM) framework within an organization?
- To reduce IT infrastructure costs
- To ensure data is accurate, complete, consistent, and fit for use (Correct answer)
- To accelerate software development cycles
- To enforce cybersecurity protocols
Correct answer: To ensure data is accurate, complete, consistent, and fit for use
A DQM framework ensures data meets quality dimensions such as accuracy, completeness, consistency, and timeliness so it is fit for its intended business purpose.
Question 2: Which of the following is NOT typically considered one of the core dimensions of data quality?
- Accuracy
- Completeness
- Scalability (Correct answer)
- Timeliness
Correct answer: Scalability
Scalability is a system architecture concept, not a data quality dimension; the core dimensions include accuracy, completeness, consistency, timeliness, validity, and uniqueness.
Question 3: A CDO discovers that 15% of customer records have duplicate entries. Which data quality dimension is most directly affected?
- Accuracy
- Timeliness
- Uniqueness (Correct answer)
- Completeness
Correct answer: Uniqueness
Uniqueness measures whether each entity is recorded only once; duplicate records directly violate this dimension.
Question 4: What is a Data Quality Scorecard primarily used for?
- Tracking employee performance in data entry roles
- Measuring and communicating data quality metrics against defined thresholds (Correct answer)
- Monitoring network bandwidth used by data pipelines
- Auditing vendor contracts for data services
Correct answer: Measuring and communicating data quality metrics against defined thresholds
A Data Quality Scorecard provides a structured way to measure, visualize, and communicate data quality metrics relative to established targets and thresholds.
Question 5: Which approach involves correcting data quality issues at the point of data entry rather than after the fact?
- Retroactive cleansing
- ETL remediation
- Prevention-based data quality control (Correct answer)
- Post-processing validation
Correct answer: Prevention-based data quality control
Prevention-based data quality control embeds validation rules and constraints at the point of capture, stopping poor-quality data from entering systems in the first place.
Question 6: A CDO wants to implement a 'single source of truth' for customer data across the enterprise. Which practice best supports this goal?
- Data replication across multiple warehouses
- Master Data Management (MDM) (Correct answer)
- Data lake consolidation without governance
- Siloed departmental databases
Correct answer: Master Data Management (MDM)
Master Data Management (MDM) creates a single, authoritative, and consistent version of key business entities like customer data, serving as the single source of truth.
Question 7: Which metric measures the percentage of data records that pass all defined quality rules?
- Data Completeness Rate
- Data Accuracy Score
- Data Quality Pass Rate (Correct answer)
- Data Freshness Index
Correct answer: Data Quality Pass Rate
The Data Quality Pass Rate (also called conformity rate) measures the percentage of records that conform to all defined quality rules and standards.
CDO Data Quality Management 1
What is the primary purpose of a Data Quality Management (DQM) framework within an organization?